ABSTRACT
Genetic linkage analysis is a collection of statistical techniques used to identify the approximate chromosomal location of disease-associated genes and other markers of interest. Numerous highly-publicized gene discoveries have included a linkage analysis step. A few examples of such discoveries include: a gene for cystic fibrosis [87, 79], a gene for Huntington’s disease [24, 26], a gene for spinal muscular atrophy [9, 56], two genes for hereditary non-polyposis colorectal cancer [71, 22, 57, 70], two genes for hereditary breast and ovarian cancer [29, 61, 99, 98], and four genes for Parkinson’s disease [75, 76, 60, 36, 18, 6, 89, 88]. For each gene discovery, I chose only one important paper with pertinent linkage results, although there may have been many papers with linkage results; for example, the entire April 1993 issue of American Journal of Human Genetics contains linkage studies of the chromosome 17 region containing the BRCA1 gene [61]. As can be seen from the above examples, while disease-gene hunting and linkage analysis have been greatly facilitated by the results of the human genome project, linkage analysis was carried out before the genome project started, and continues today after most of the human sequence is complete. Because some genetic linkage analysis computations may take a long time to run, a few computational biologists have been interested in the algorithmic problems that arise in those computations.
